An investigation about joint life policy's premium using Copula; The Case study of an insurance company in Iran

A copula is a function that links univariate marginal's to their full multivariate distribution. Copulas were introduced in 1959 in the context of probabilistic metric spaces. Copula models are becoming increasingly popular for modeling dependencies between random variables. The ranges of their recent applications include such fields as analysis of extremes in financial assets and returns, failure of paired organs in health science, and human mortality in insurance. Our contribution in this paper is to introduce joint life insurance as it is not offered by Iranian insurance companies. We are going to show importance and usefulness of this policy for both insurer and insured. For this reason, we use copula in order to calculate joint life insurance premiums by applying appropriate actuarial formulas using MATLAB and SPSS software. Based on our findings, a joint life insurance premium is lower than the sum of two policies which is bought separately. This means that insurers can charge lower premiums which enable them to increase their market share. On the other hand, lower premiums can increase customer's welfare.